Document Type

Journal Article

Publisher

Hindawi Limited

School

School of Science

RAS ID

26593

Comments

Originally published as :

Yang, W., Hu, J., Wang, S., & Wu, Q. (2018). Biometrics Based Privacy-Preserving Authentication and Mobile Template Protection. Wireless Communications and Mobile Computing, 2018, 17 pages. Article can be found here

Abstract

Smart mobile devices are playing a more and more important role in our daily life. Cancelable biometrics is a promising mechanism to provide authentication to mobile devices and protect biometric templates by applying a noninvertible transformation to raw biometric data. However, the negative effect of nonlinear distortion will usually degrade the matching performance significantly, which is a nontrivial factor when designing a cancelable template. Moreover, the attacks via record multiplicity (ARM) present a threat to the existing cancelable biometrics, which is still a challenging open issue. To address these problems, in this paper, we propose a new cancelable fingerprint template which can not only mitigate the negative effect of nonlinear distortion by combining multiple feature sets, but also defeat the ARM attack through a proposed feature decorrelation algorithm. Our work is a new contribution to the design of cancelable biometrics with a concrete method against the ARM attack. Experimental results on public databases and security analysis show the validity of the proposed cancelable template.

DOI

10.1155/2018/7107295

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

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